4 citations · 4 across the 8 of their papers we have counts for
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cs.AI2026
Adaptive-Group Process Rewards for GUI Agents
Zirui Shang, Yang Liu, Xin Shu +3
Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process rewards offer a promising d…
cs.AI2026
Interactive Reward Agent: GUI Task Evaluation via Environment-State Verification
Chenrui Shi, Yuwei Wu, Yang Liu +5
Graphical user interface task evaluation aims to determine whether a GUI agent has successfully completed a user instruction. Automated GUI task evaluation has received increasing…
cs.AI2026
GUIDE: Resolving Domain Bias in GUI Agents through Real-Time Web Video Retrieval and Plug-and-Play Annotation
Rui Xie, Zhi Gao, Chenrui Shi +3
Large vision-language models have endowed GUI agents with strong general capabilities for interface understanding and interaction. However, due to insufficient exposure to domain-s…